Balanced and Swap-Robust Trades for Dynamical Distributed Storage

Trades, introduced by Hedayat [9], are two sets of blocks of elements which may be exchanged (traded) without altering the counts of certain subcollections of elements within their constituent blocks. They are of importance in applications where certain combinations of elements dynamically become prohibited from being placed in the same group of elements, since in this case one can trade the offending blocks with allowed ones. This is particularly the case in distributed storage systems, where due to privacy and other constraints, data of some groups of users cannot be stored together on the same server. We introduce a new class of balanced trades, important for access balancing of servers, and perturbation resilient balanced trades, important for studying the stability of server access frequencies with respect to changes in data popularity. The constructions and bounds on our new trade schemes rely on specialized selections of defining sets in minimal trades and number-theoretic analyses.

[1]  Charles J. Colbourn,et al.  Access balancing in storage systems by labeling partial Steiner systems , 2019, Designs, Codes and Cryptography.

[2]  Natalia Silberstein,et al.  Optimal combinatorial batch codes based on block designs , 2016, Des. Codes Cryptogr..

[3]  Dimitris S. Papailiopoulos,et al.  Locality and Availability in Distributed Storage , 2014, IEEE Transactions on Information Theory.

[4]  Charles J. Colbourn,et al.  Egalitarian Steiner triple systems for data popularity , 2021, Designs, Codes and Cryptography.

[5]  Olgica Milenkovic,et al.  Probabilistic Transforms for Combinatorial Urn Models , 2004, Combinatorics, Probability and Computing.

[6]  Emina Soljanin,et al.  On the Delay-Storage Trade-Off in Content Download from Coded Distributed Storage Systems , 2013, IEEE Journal on Selected Areas in Communications.

[7]  Ludmila Cherkasova,et al.  Analysis of enterprise media server workloads: access patterns, locality, content evolution, and rates of change , 2004, IEEE/ACM Transactions on Networking.

[8]  Emina Soljanin,et al.  Evaluating Load Balancing Performance in Distributed Storage With Redundancy , 2019, IEEE Transactions on Information Theory.

[9]  Alexandros G. Dimakis,et al.  Distributed Storage Allocations , 2010, IEEE Transactions on Information Theory.

[10]  Alexandros G. Dimakis,et al.  Network Coding for Distributed Storage Systems , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[11]  A. S. Hedayat,et al.  The theory of trade-off for t -designs , 1990 .

[12]  H. L. Hwang On the structure of (v,k,t) trades , 1986 .

[13]  William M. Brummond Kirkman Systems that Attain the Upper Bound on the Minimum Block Sum, for Access Balancing in Distributed Storage , 2019 .

[14]  Kannan Ramchandran,et al.  Fractional repetition codes for repair in distributed storage systems , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[15]  Hoang Dau,et al.  MaxMinSum Steiner Systems for Access-Balancing in Distributed Storage , 2017, SIAM J. Discret. Math..

[16]  Natalia Silberstein,et al.  Optimal Fractional Repetition Codes Based on Graphs and Designs , 2014, IEEE Transactions on Information Theory.